The Moderating Role of Workforce Education in the AI Exposure-Tobin's Q Relationship of Listed Firms

Abstract

The rapid diffusion of artificial intelligence (AI) is reshaping how firms create value. Although a growing literature examines the economic consequences of AI, relatively little attention has been paid to how human capital conditions the relationship between AI exposure and firm value. Based on the pro-worker AI framework advanced by Acemoglu, Autor, and Johnson, this study aims to examine whether employee education conditions the relationship between AI exposure and firm value among Chinese listed firms. By using 5,140 firm-year observations from the CSMAR database, it measures Tobin's Q and constructs firm-level measures of AI exposure and employee education. To test these relationships, a cross-sectional OLS model with interaction terms is employed to examine whether employee education and firm size moderate the association between AI exposure and firm value. The results show a positive association between AI exposure and Tobin's Q. The interaction between EDU and AI exposure is positive and significant, indicating that the association between AI exposure and firm value is stronger among firms with higher levels of employee education. In contrast, the interaction between AI exposure and asset size is not statistically significant, suggesting that firm size does not significantly alter the AI-value association in this sample. These findings indicate that workforce characteristics should be considered when evaluating the market implications of AI exposure.